Recently, Graph Convolutional Network (GCN) [1]} has been adopted to model long-range relationships in images [2]}, [3]}, [4]} and videos [5]}.
Given highly-overlapping objects, pixels belonging to the same partially occluded object may be separated into disjoint subregions by the occluder.
Thus, we adopt GCN as our basic block due to its non-local property [6]}, where each graph node represents a single pixel on the feature map.
To explicitly model the occluding region, we further extend the single GCN block to the bilayer GCN structure as shown in Figure REF , which constructs two orthogonal graphs in a single general framework.
